Posts Tagged ‘AIAgents’
[DotJs2025] Modern Day Mashups: How AI Agents are Reviving the Programmable Web
Nostalgia’s glow recalls Web 2.0’s mashup mania—APIs alchemized into novelties, Google Maps wedding Craigslist for HousingMaps’ geospatial grace. Angie Jones, Block’s global VP of developer relations and 27-patent savant, resurrected this renaissance at dotJS 2025, heralding AI agents as programmable web’s phoenix via MCP (Model Context Protocol). An IBM Master Inventor turned educator, Angie’s odyssey—from virtual worlds to Azure’s principal—now orchestrates Goose, Block’s open-source agent, mashing MCPs for emergent enchantments.
Angie’s arc: 2000s’ closed gardens yielded to API avalanches—crime overlays, restaurant radars—yet silos stifled. AI’s advent: agents as conductors, LLMs querying MCPs—modular connectors to calendars, codebases, clouds. Goose’s genesis: MCP client, extensible via SDKs, wielding refs like filesystem fetches or GitHub grapples. Demos dazzled: Slack summons, Drive dossiers, all agent-autonomous—prompts birthing behaviors, mashups manifesting sans scaffolding.
MCP’s mosaic: directories like Glama AI’s report cards (security scores, license litmus), PostMCP’s popularity pulses, Block’s nascent registry—metadata-rich, versioned vaults. 2025’s swell: thousands tally, community curating—creators crafting custom conduits, from Figma flows to Figma fusions. Angie’s axiom: revive 2000s’ whimsy, amplified—productivity’s polish, creativity’s canvas—democratized by open forges.
This resurgence: agents as artisans, web as workshop—mash to manifest, share to spark.
Mashup’s Metamorphosis
Angie animated epochs: HousingMaps’ heuristic hacks to MCP’s modular might—agents querying conduits, emergent apps from elemental exchanges. Goose’s grace: SDK-spawned servers, refs routing realms—Slack’s summons, Drive’s deluge.
MCP’s Marketplace and Momentum
Directories discern: Glama’s grades, PostMCP’s pulses—Block’s beacon unifying. Thousands thrive, tinkerers tailoring—Figma to finance, fun’s frontier.
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[DotAI2024] DotAI 2024: Stanislas Polu – Tracing the Evolution of LLM Reasoning and Agency
Stanislas Polu, a trailblazing researcher and co-founder of Dust, offered a panoramic view of large language models’ ascent at DotAI 2024. With a background spanning Polytechnique, Stanford, and pivotal roles at Stripe and OpenAI—where he advanced mathematical reasoning in LLMs—Polu now steers Dust toward AI-augmented enterprise tools. His discourse framed the AI epoch as a societal phase shift, paralleling seismic transitions like agriculture or electrification, and dissected how LLMs’ cognitive prowess is reshaping work and innovation.
Societal Shifts Catalyzed by Emergent Intelligence
Polu likened the pre- to post-AI era to historical ruptures, pinpointing AlphaZero’s 2017 debut as the inflection. This system, ingesting mere rules to master Go and chess beyond human bounds, evoked extraterrestrial ingenuity—crunching simulations to forge strategies unattainable through rote play. ChatGPT’s 2022 emergence amplified this, birthing agents that orchestrate tasks autonomously, while recent milestones like an AI securing a bronze at the International Mathematical Olympiad signal prowess in abstract deduction.
These strides, Polu observed, provoke institutional ripples: Nobel nods to AI-driven physics and biology breakthroughs affirm computation’s ascendancy in discovery. Yet, deployment lags potential; in mid-2022, OpenAI’s revenues hovered in tens of millions, with scant workplace adoption. This chasm propelled Polu’s pivot from research to product, hypothesizing that interfaces, not algorithms, bottleneck utility.
Dust embodies this thesis, granting teams bespoke assistants attuned to proprietary data and actions. Unlike monolithic bots, specialized agents—narrowly scoped for tasks like query resolution or report synthesis—yield superior accuracy by mitigating retrieval noise and model hallucinations. Polu’s narrative stresses infrastructure’s role: plumbing data silos and action endpoints to empower models without exposing sensitivities.
Unlocking Workplace Transformation Through Tailored AI
At Dust’s core lies dual convictions: seamless enterprise integration and multiplicity of agents. The former demands robust pipes—secure data federation and API orchestration—while the latter champions modularity, where assistants evolve via iterative refinement, drawing from domain lore to eclipse generalists.
Polu recounted Dust’s genesis amid GPT’s hype, yet workplace AI remains nascent, mired in “pre-GPT” paradigms of siloed tools. His solution: hyper-focused agents that ingest contextual artifacts, execute workflows, and iterate on feedback loops. This architecture not only boosts efficacy but fosters emergent behaviors, like chaining assistants for complex pipelines.
Envision a sales team querying leads enriched by CRM insights, or engineers debugging via code-aware bots—scenarios where Dust’s agnosticism across models ensures longevity. Polu advocated starting small: automate a 30-minute drudgery with GPT or Dust, scaling from there. This pragmatic ethos, he contended, unlocks boundless augmentation, where AI amplifies human ingenuity rather than supplants it.
As enterprises grapple with AI’s dual-edged sword—efficiency gains versus integration hurdles—Polu’s blueprint charts a collaborative path. Dust’s trajectory, blending research rigor with product agility, heralds a workspace where intelligence permeates, propelling productivity into uncharted realms.